Dissecting the Role of Edge AI within a Smart Building

Chris Penrose
Chris Penrose

Chris Penrose, COO, FogHorn explains the benefits of AI-enabled edge computing in a modern building.

From serving as a physical space to work or live in to providing a building experience for tenants to thrive, the definition and functions of a modern building have evolved over the last couple decades. Innovative technology and accelerated digital transformations, partially due to COVID-19, have played a key role in creating the capabilities that make-up a smart building today. These innovative technologies include AI-enabled edge computing, or edge AI, which has played a critical part in augmenting existing building management systems (BMSs) through cost-effective and efficient approach.

As the adoption and capabilities of internet of things (IoT) devices and sensors continue to increase within smart buildings, so does the amount of information collected, that operators can leverage to improve overall efficiency and increase bottom line savings. However, sending these ever-increasing amounts of IoT data to the cloud for processing to produce actionable insights comes at a cost and introduces latency, which inhibits an organization’s ability to act on insights powered by real-time processing. Edge AI allows data to be processed on site, near the source of the data, eliminating the need for cloud processing and therefore providing real-time actionable insights for both cost-savings and increased operational efficiency to improve smart building functions. This results in increased accuracy and faster production of valuable insights. This rapid processing and insight production can be applied on top of existing BMSs to enhance a myriad of building functions -- including energy management, predictive maintenance of assets, and health and safety monitoring.

Energy Management

Currently, BMSs are solely used for observational purposes, rather than applying actions to resolve the challenges that surface from such observations. To enhance their current BMS, building managers can leverage edge AI platforms to perform machine learning (ML) and AI at the edge to make optimal adjustments in real-time in order to adapt to ever-changing environmental factors, such as the atmospheric temperature or occupancy of a building. Building managers are then able to obtain relevant insights from data streams and address issues more effectively, while factoring in occupancy safety and comfort for matters that could potentially impact the tenant experience -- such as scheduling maintenance. Building managers can prevent any unplanned downtime from arising with the ability to predict power and utility outages, or surges, through the use of edge AI energy management solutions.

By collecting data from a multitude of sensors and environmental factors -- e.g. temperature, humidity and occupancy sensors, weather forecasts and time-of-day energy rates, edge AI platforms can take energy management to a whole new level to optimize functions such as heating and cooling, airflow circulation and lighting. This approach results in a cost-effective smart energy conservation strategy, helping cut costs associated with data transmission, bandwidth constraints and related computational costs. As a budget-friendly method for monitoring energy usage, edge AI platforms can adjust BMSs 24/7 to fit the activity levels and needs of a building or building space.

Predictive Maintenance

Building managers can also improve BMS capabilities with edge AI to enable predictive and prescriptive maintenance, in order to identify potential risks based on equipment condition. Edge AI platforms can monitor the operational data gathered from the machines and through additional sensors, like high-frequency vibration sensors, and apply advanced analytics in real-time to predict failures. If a potential failure is detected, the system can automatically intervene by sending signals to the control units, as well as alert building managers, to repair or replace equipment (e.g. chillers) based on current machine health and maintenance models. By utilizing this information, building managers can proactively schedule and conduct maintenance services, resulting in reducing the amount of unplanned downtime and improving overall building efficiency. This also enables building managers to provide unprecedented levels of proactive service for building occupants -- creating a more convenient, entrusted and comfortable working or living experience. Long-term benefits of predictive maintenance also include maximizing effective asset lifetime for expensive equipment (e.g. HVAC systems) and significantly reducing major failures and downtime that could otherwise prove detrimental to a business’ performance.

Health & Safety Monitoring

Edge AI platforms can also help mitigate the chances of power outages, broken elevators or fire alarms, to provide a safer environment for their tenants to live and work in. For instance, edge AI can augment a building’s security system to monitor security camera footage through the use of machine vision, streaming video analytics and infrared or video cameras. By doing so, building managers can identify safety threats, such as unauthorized building area access or even a hazardous gas leak through infrared cameras or air quality monitors.

Taking safety monitoring one step further, edge AI can also be paired with video and audio analytics to provide actionable insights about active health and safety threats within a building. Employees throughout the manufacturing industry filed hundreds of worker safety lawsuits in 2020, with 68% of workers around the world reporting not feeling completely safe at work. As more organizations return to in-person operations, the stakes are higher than ever before for building managers to provide effective and efficient health and safety monitoring systems to protect the tenants. Furthermore, as states begin to ease COVID-19 mandates and the number of people allowed within an indoor space begin to increase, so will the amount of health and safety monitoring data needing to be processed.

In order to avoid the hefty costs and delayed insights associated with sending these mass amounts of data back to the cloud for processing, as well as potential security risks, building managers are leveraging edge AI with real-time analytics. From there, edge AI can be combined with live audio and video streams from thermal and RGB cameras to detect potential health issues such as elevated body temperatures or proper PPE usage (E.g., masks and other facial coverings) as they occur. If a health and safety policy violation occurs, the edge AI platform can generate and send a real-time alert to relevant staff to take action. 

 

The Future of BMSs

As our world inevitably continues to evolve at a rapid pace, so will our demands for a more integrated building experience -- and it’s important that our workplaces and living environments evolve with it. Edge AI enabled buildings will continue to play a critical role in transforming our day-to-day operations but the real-time capabilities of edge AI will provide building managers with the insights they need to resolve issues in a timely, cost-effective and efficient manner. Edge AI will continue to empower building managers through the production of valuable, actionable insights from live, streaming data to understand the operations within their building - e.g. energy usage to increase energy efficiency -- therefore, optimize building operations to support energy saving initiatives.

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